Data Field for Hierarchical Clustering

2011 ◽  
Vol 7 (4) ◽  
pp. 43-63 ◽  
Author(s):  
Shuliang Wang ◽  
Wenyan Gan ◽  
Deyi Li ◽  
Deren Li
Keyword(s):  
Hierarchical Clustering ◽  
Physical Space ◽  
Core Data ◽  
Data Object ◽  
Group Data ◽  
Data Field ◽  
Data Objects ◽  
The Masses ◽  
Space Data ◽  
The Impact

In this paper, data field is proposed to group data objects via simulating their mutual interactions and opposite movements for hierarchical clustering. Enlightened by the field in physical space, data field to simulate nuclear field is presented to illuminate the interaction between objects in data space. In the data field, the self-organized process of equipotential lines on many data objects discovers their hierarchical clustering-characteristics. During the clustering process, a random sample is first generated to optimize the impact factor. The masses of data objects are then estimated to select core data object with nonzero masses. Taking the core data objects as the initial clusters, the clusters are iteratively merged hierarchy by hierarchy with good performance. The results of a case study show that the data field is capable of hierarchical clustering on objects varying size, shape or granularity without user-specified parameters, as well as considering the object features inside the clusters and removing the outliers from noisy data. The comparisons illustrate that the data field clustering performs better than K-means, BIRCH, CURE, and CHAMELEON.

Data Field for Hierarchical Clustering

2013 ◽  
pp. 303-324
Author(s):  
Shuliang Wang ◽  
Wenyan Gan ◽  
Deyi Li ◽  
Deren Li
Keyword(s):  
Hierarchical Clustering ◽  
Physical Space ◽  
Core Data ◽  
Data Object ◽  
Self Organized ◽  
Data Field ◽  
Data Objects ◽  
The Masses ◽  
Space Data ◽  
Object Features

In this paper, data field is proposed to group data objects via simulating their mutual interactions and opposite movements for hierarchical clustering. Enlightened by the field in physical space, data field to simulate nuclear field is presented to illuminate the interaction between objects in data space. In the data field, the self-organized process of equipotential lines on many data objects discovers their hierarchical clustering-characteristics. During the clustering process, a random sample is first generated to optimize the impact factor. The masses of data objects are then estimated to select core data object with nonzero masses. Taking the core data objects as the initial clusters, the clusters are iteratively merged hierarchy by hierarchy with good performance. The results of a case study show that the data field is capable of hierarchical clustering on objects varying size, shape or granularity without user-specified parameters, as well as considering the object features inside the clusters and removing the outliers from noisy data. The comparisons illustrate that the data field clustering performs better than K-means, BIRCH, CURE, and CHAMELEON.

scholarly journals OPTIMASI PSO UNTUK METODE CLUSTERING FUZZY C-MEANS DALAM PENGELOMPOKAN KELAS

Petir ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 72-91
Author(s):  
Redaksi Tim Jurnal
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
High Dimensional ◽  
Swarm Optimization ◽  
Fuzzy C Means ◽  
Data Object ◽  
Local Solutions ◽  
Data Objects ◽  
The Impact ◽  
Selection Of

Clustering is a method that divides data objects into groups based on information found in data describing objects and relationships between them. In partition-based cluster analysts K-Means method and Fuzzy CMeans Method which is a frequent and commonly used clustering method. However, in its development now with various macar data with the complexity of the variable would be more asked again to the effectiveness and as efficiently whether the method can cluster the data. So it is necessary to optimize where the method has a weakness that is likely to mask the impact of the deficiency in clustering a data object that has a complex variable. Data data used is the value of slot shift one with a variable of the value Academic, nonacademic value in the form of a questionnaire value attitudes assessed by each teacher will be inputted, as a determinant of the division of leading classes in the future in the next teaching. In this study tried to correct some of the deficiencies of the Fuzzy C-Means algorithm ie the selection of early cluster centers and local solutions. An efficient algorithm is proposed to improve the grouping of such methods with Particle Swarm Optimization. In recent years, Particle Swarm Optimization (PSO) has been successfully applied to a number of real-world grouping issues with fast and effective convergence for high-dimensional data.

scholarly journals The Impact of COVID-19 Pandemic and Lockdown Measures on Quality of Life among Italian General Population

2021 ◽  
Vol 10 (2) ◽  
pp. 289 ◽  
Author(s):  
Maria Stella Epifanio ◽  
Federica Andrei ◽  
Giacomo Mancini ◽  
Francesca Agostini ◽  
Marco Andrea Piombo ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Online Survey ◽  
Physical Space ◽  
Sampling Strategy ◽  
World Health ◽  
Snowball Sampling ◽  
World Health Organization Quality ◽  
The World ◽  
The Impact

The COVID-19 pandemic that has hit the world in the year 2020 has put a strain on our ability to cope with events and revolutionized our daily habits. On 9 March, Italy was forced to lockdown to prevent the spread of the infection, with measures including the mandatory closure of schools and nonessential activities, travel restrictions, and the obligation to spend entire weeks in the same physical space. The aim of this study was to assess the impact of the COVID-19 pandemic and lockdown measures on quality of life (QoL) in a large Italian sample, in order to investigate possible differences in QoL levels related to both demographic and pandemic-specific variables. A total of 2251 Italian adults (1665 women, mainly young and middle adults) were recruited via a snowball sampling strategy. Participants were requested to answer to an online survey, which included demographic and COVID-related information items, and the World Health Organization Quality of Life BREF questionnaire (WHOQOL-BREF). The results showed statistically significant differences in QoL depending on a number of variables, including sex, area of residence in Italy, and being diagnosed with a medical/psychiatric condition. To our knowledge, this is the first study to assess QoL during COVID-19 pandemic in Italy, therefore the present findings can offer guidelines regarding which social groups are more vulnerable of a decline in QoL and would benefit of psychological interventions.

scholarly journals Exogenous Alginate Protects Staphylococcus aureus from Killing by Pseudomonas aeruginosa

2019 ◽  
Vol 202 (8) ◽  
Author(s):  
Courtney E. Price ◽  
Dustin G. Brown ◽  
Dominique H. Limoli ◽  
Vanessa V. Phelan ◽  
George A. O’Toole
Keyword(s):  
Staphylococcus Aureus ◽  
Pseudomonas Aeruginosa ◽  
Physical Space ◽  
Late Time ◽  
Protective Effects ◽  
Content Type ◽  
Alginate Production ◽  
The Impact

ABSTRACT Cystic fibrosis (CF) patients chronically infected with both Pseudomonas aeruginosa and Staphylococcus aureus have worse health outcomes than patients who are monoinfected with either P. aeruginosa or S. aureus. We showed previously that mucoid strains of P. aeruginosa can coexist with S. aureus in vitro due to the transcriptional downregulation of several toxic exoproducts typically produced by P. aeruginosa, including siderophores, rhamnolipids, and HQNO (2-heptyl-4-hydroxyquinoline N-oxide). Here, we demonstrate that exogenous alginate protects S. aureus from P. aeruginosa in both planktonic and biofilm coculture models under a variety of nutritional conditions. S. aureus protection in the presence of exogenous alginate is due to the transcriptional downregulation of pvdA, a gene required for the production of the iron-scavenging siderophore pyoverdine as well as the downregulation of the PQS (Pseudomonas quinolone signal) (2-heptyl-3,4-dihydroxyquinoline) quorum sensing system. The impact of exogenous alginate is independent of endogenous alginate production. We further demonstrate that coculture of mucoid P. aeruginosa with nonmucoid P. aeruginosa strains can mitigate the killing of S. aureus by the nonmucoid strain of P. aeruginosa, indicating that the mechanism that we describe here may function in vivo in the context of mixed infections. Finally, we investigated a panel of mucoid clinical isolates that retain the ability to kill S. aureus at late time points and show that each strain has a unique expression profile, indicating that mucoid isolates can overcome the S. aureus-protective effects of mucoidy in a strain-specific manner. IMPORTANCE CF patients are chronically infected by polymicrobial communities. The two dominant bacterial pathogens that infect the lungs of CF patients are P. aeruginosa and S. aureus, with ∼30% of patients coinfected by both species. Such coinfected individuals have worse outcomes than monoinfected patients, and both species persist within the same physical space. A variety of host and environmental factors have been demonstrated to promote P. aeruginosa-S. aureus coexistence, despite evidence that P. aeruginosa kills S. aureus when these organisms are cocultured in vitro. Thus, a better understanding of P. aeruginosa-S. aureus interactions, particularly mechanisms by which these microorganisms are able to coexist in proximal physical space, will lead to better-informed treatments for chronic polymicrobial infections.

Optimal Capacitors Placement of Distribution Systems Using 2nd Order Power Loss Sensitivity Analysis and Hierarchical Clustering

2014 ◽  
Vol 986-987 ◽  
pp. 377-382 ◽  
Author(s):  
Hui Min Gao ◽  
Jian Min Zhang ◽  
Chen Xi Wu
Keyword(s):  
Sensitivity Analysis ◽  
Hierarchical Clustering ◽  
Distribution System ◽  
Power Flow ◽  
Distribution Systems ◽  
Reactive Power ◽  
Digital Simulation ◽  
Second Order ◽  
First Order ◽  
The Impact

Heuristic methods by first order sensitivity analysis are often used to determine location of capacitors of distribution power system. The selected nodes by first order sensitivity analysis often have virtual high by first order sensitivities, which could not obtain the optimal results. This paper presents an effective method to optimally determine the location and capacities of capacitors of distribution systems, based on an innovative approach by the second order sensitivity analysis and hierarchical clustering. The approach determines the location by the second order sensitivity analysis. Comparing with the traditional method, the new method considers the nonlinear factor of power flow equation and the impact of the latter selected compensation nodes on the previously selected compensation location. This method is tested on a 28-bus distribution system. Digital simulation results show that the reactive power optimization plan with the proposed method is more economic while maintaining the same level of effectiveness.

Impacts of the COVID-19 pandemic on protected area management and conservation outcomes in Mexico

2021 ◽  
Author(s):  
Kathryn Powlen ◽  
Kelly W. Jones ◽  
Elva Ivonne Bustamante Moreno ◽  
Maira Abigail Ortíz Cordero ◽  
Jennifer N. Solomon ◽  
...  
Keyword(s):  
Management Support ◽  
Short Term ◽  
Group Data ◽  
Management Capacity ◽  
Focus Group Data ◽  
Technical Capacity ◽  
The Impact ◽  
Relief Efforts ◽  
Management And Conservation

Protected areas (PAs) are under immense pressure to safeguard much of the world’s remaining biodiversity and can be strained by unpredicted events such as the COVID-19 pandemic. Understanding the extent of the pandemic on PA inputs, mechanisms, and conservation outcomes is critical for recovery and future planning to buffer against these types of events. We use survey and focus group data to quantify the impact of the pandemic on Mexico’s PA network and outline the pathways that led to conservation outcomes. On average, across 62 PAs, we find substantial changes in management capacity, monitoring, and tourism, and a slight increase in non-compliant activities. Our findings highlight the need to increase short-term relief efforts and long-term livelihood diversification initiatives for communities dependent on tourism, who were most vulnerable during the pandemic. Increased management support, including technical capacity and financial resources, could also better sustain management activities in future shocks.

A Study on impact of smartphone addiction on academic performance

2018 ◽  
Vol 7 (2.6) ◽  
pp. 50 ◽  
Author(s):  
Pamela Chaudhury ◽  
Hrudaya Kumar Tripathy
Keyword(s):  
Academic Performance ◽  
Negative Impact ◽  
Pearson Correlation ◽  
Machine Learning Techniques ◽  
Smartphone Addiction ◽  
Active Involvement ◽  
Outdoor Sports ◽  
Using Data ◽  
The Masses ◽  
The Impact

Smartphone addiction is increasingly affecting the masses and is negatively impacting the younger generation. Several researches have been done to study the impact of internet and smartphone addiction. However no work has been done to predetermine academic performance from smartphone addiction using data mining techniques. A total of 222 University students participated in the questionnaire. The survey questionnaire consisted of demographic information, internet access pattern and smartphone addiction pattern. Data was analysed using machine learning techniques using classification models. The results further encouraged us to find the correlation between smartphone addiction and academic performance. Pearson’ correlation was used to establish that smartphone usage had a negative impact on academic performance. Additionally other attributes like internet connectivity and active involvement in outdoor sports activities were investigated. Experimental results confirmed a negative correlation of these attributes with academic performance. The findings were of immense use and could be used to reduce the internet addiction amongst the student community and also enhance their academic performance

Languages on Stage: Linguistic Pluralism and Community Formation in the Nineteenth-Century Parsi Theatre

2003 ◽  
Vol 37 (2) ◽  
pp. 381-405 ◽  
Author(s):  
Kathryn Hansen
Keyword(s):  
Catalytic Effect ◽  
Community Formation ◽  
Economic Base ◽  
Modern Drama ◽  
Dominant Form ◽  
Middle Classes ◽  
Indian Cinema ◽  
The Masses ◽  
Commercial Organization ◽  
The Impact

The Parsi theatre was the dominant form of dramatic entertainment in urban India from the 1860s to the 1930s. Named for its Bombay-based pioneers, the Parsi theatre blended certain European practices of stagecraft and commercial organization with Indic, Persian, and English stories, music, and poetry. Through the impact of its touring companies, it had a catalytic effect on the development of modern drama and regional theatre throughout South and Southeast Asia. Moreover, Parsi theatre is widely credited with contributing to popular Indian cinema its genres, aesthetic, and economic base. With Hindi films now the major cultural signifier for the middle classes and the ‘masses’ in South Asia and its diaspora, documentation and evaluation of the Parsi theatre is much needed, especially to connect it convincingly to the cinematic medium that followed.

scholarly journals Small impacts on the giant planet Jupiter

2018 ◽  
Vol 617 ◽  
pp. A68 ◽  
Author(s):  
R. Hueso ◽  
M. Delcroix ◽  
A. Sánchez-Lavega ◽  
S. Pedranghelu ◽  
G. Kernbauer ◽  
...  
Keyword(s):  
Giant Planet ◽  
Interplanetary Dust ◽  
Light Curves ◽  
Dust Particles ◽  
Video Observation ◽  
Interplanetary Dust Particles ◽  
The Past ◽  
Giant Impacts ◽  
The Masses ◽  
The Impact

Context. Video observations of Jupiter obtained by amateur astronomers over the past 8 years have shown five flashes of light with durations of 1–2 s, each observed by at least two observers that were geographically separated. The first three of these events occurred on 3 June 2010, 20 August 2010, and 10 September 2012. Previous analyses of their light curves showed that they were caused by the impact of objects of 5–20 m in diameter, depending on their density, with a released energy comparable to superbolides on Earth of the class of the Chelyabinsk airburst. The most recent two flashes on Jupiter were detected on 17 March 2016 and 26 May 2017 and are analyzed here. Aims. We characterize the energy involved together with the masses and sizes of the objects that produced these flashes. The rate of similar impacts on Jupiter provides improved constraints on the total flux of impacts on the planet, which can be compared to the amount of exogenic species detected in the upper atmosphere of Jupiter. Methods. We extracted light curves of the flashes and calculated the masses and sizes of the impacting objects after calibrating each video observation. We also present results from a systematic search of impacts on >72 000 video amateur observations with a customized software that is based on differential photometry of the images. An examination of the number of amateur observations of Jupiter as a function of time over the past years allows us to interpret the statistics of these impact detections. Results. The cumulative flux of small objects (5–20 m or larger) that impact Jupiter is predicted to be low (10–65 impacts per year), and only a fraction of them are potentially observable from Earth (4–25 observable impacts per year in a perfect survey). These numbers imply that many observers are required to efficiently discover Jupiter impacts. Conclusions. We predict that more impacts will be found in the next years, with Jupiter opposition displaced toward summer in the northern hemisphere where most amateur astronomers observe. Objects of this size contribute negligibly to the abundance of exogenous species and dust in the stratosphere of Jupiter when compared with the continuous flux from interplanetary dust particles punctuated by giant impacts. Flashes of a high enough brightness (comparable at their peak to a +3.3 magnitude star) could produce an observable debris field on the planet. We estimate that a continuous search for these impacts might find these events once every 0.4–2.6 yr.

scholarly journals Classroom Re-design to Facilitate Student Learning: A Case Study of Changes to a University Classroom

2016 ◽  
Vol 16 (1) ◽  
pp. 53-68 ◽  
Author(s):  
Tom Perks ◽  
Doug Orr ◽  
Elham Al-Omari
Keyword(s):  
Student Satisfaction ◽  
Physical Environment ◽  
Teaching And Learning ◽  
Physical Space ◽  
Learning Space ◽  
Effective Learning ◽  
Group Data ◽  
Focus Group Data ◽  
Teaching Learning

This case study examines the physical aspects of a particular university classroom, and what affect specific changes to the classroom had on the perceptions of students, instructors and observers regarding the room as an effective learning space. We compare survey and focus group data collected from students taking courses in the classroom prior to changes to the physical environment with comparable data from students taking courses in the same classroom after specific changes had been made. Immediately following changes to the classroom, notable increases were observed in reported perceptions of student satisfaction with the physical environment, including perceptions of the classroom as a more effective and engaging learning space. Similar perceptions of improvement as a teaching-learning space were reported by instructors and observers. However, subsequent follow-up data collection and analyses suggested little if any sustained increase in perceptions of efficacy of the room as a learning space; indeed, most reported variables returned to baseline levels. The implications of these findings and their relevance to classroom design nevertheless may provide insight regarding the manner in which physical space might support or even enhance teaching and learning.

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